Abstract: Academic advisors assist students in academic, professional, social and personal matters. Successful advising increases student retention, improves graduation rates and helps students meet educational goals. This work presents an advising system that assists advisors in multiple tasks using natural language. This system features a conversational agent as the user interface, an academic advising knowledge base with a method to allow the users to contribute to it, an expert system for academic planning, and a web design structure for the implementation platform. The system is operational for several hundred students from a university department. The system performed well, obtaining close to 80%, on the traditional language processing measures of precision, recall, accuracy and F1 score. Assessment from the constituencies showed positive and assuring reviews. This work provides an assessment and technological solution to the academic advising field, i.e., the first-known advising multi-task conversational system with adaptive measures for improvement. The evaluation in a real-world scenario shows its viability, and initiated the development of a corpus for academic advising, valuable for the academic and language processing research communities.